Combined epigenetic/genetic study identified an ALS age of onset modifier

Age at onset of amyotrophic lateral sclerosis (ALS) is highly variable (eg, 27–74 years in carriers of the G4C2-expansion in C9orf72). It might be influenced by environmental and genetic factors via the modulation of DNA methylation (DNAm) at CpG-sites. Hence, we combined an epigenetic and genetic approach to test the hypothesis that some common single nucleotide polymorphisms (SNPs) at CpG-sites (CpG-SNPs) could modify ALS age of onset. Our genome-wide DNAm analysis suggested three CpG-SNPs whose DNAm levels are significantly associated with age of onset in 249 ALS patients (q < 0.05). Next, genetic analysis validated the association of rs4970944 with age of onset in the discovery (n = 469; P = 0.025) and replication (n = 4160; P = 0.007) ALS cohorts. A meta-analysis of the cohorts combined showed that the median onset in AA-carriers is two years later than in GG-carriers (n = 4629; P = 0.0012). A similar association was observed with its tagging SNPs, implicating a 16 Kb region at the 1q21.3 locus as a modifier of ALS age of onset. Notably, rs4970944 genotypes are also associated with age of onset in C9orf72-carriers (n = 333; P = 0.025), suggesting that each A-allele delays onset by 1.6 years. Analysis of Genotype-Tissue Expression data revealed that the protective A-allele is linked with the reduced expression of CTSS in cerebellum (P = 0.00018), which is a critical brain region in the distributed neural circuits subserving motor control. CTSS encodes cathepsin S protein playing a key role in antigen presentation. In conclusion, we identified a 16 Kb locus tagged by rs4970944 as a modifier of ALS age of onset. Our findings support the role of antigen presenting processes in modulating age of onset of ALS and suggest potential drug targets (eg, CTSS). Future replication studies are encouraged to validate the link between the locus tagged by rs4970944 and age of onset in independent ALS cohorts, including different ethnic groups. Supplementary Information The online version contains supplementary material available at 10.1186/s40478-021-01183-w.

Candidate CpG-SNPs with significant association between their DNAm level and age of onset in 249 ALS patients.
3 Table S2 Results of the subgroup analysis in Canadian ALS patients (n=469) and US ALS patients (n=4160).
3 Table S4 eQTL analysis using the GTEx database revealed significant changes in gene expression associated with rs4970944 in different tissues (normalized effect size (NES) are listed).

Fig. S8
Meta-analysis of the adjusted regression coefficient from the discovery cohort (n=469) and the replication cohort (n=3697) in C9orf72 negative ALS patients.

Supplementary acknowledgements
Acknowledgements for using the dbGap dataset. 10 -11 Table S1. Candidate CpG-SNPs with significant association (in bold) between their DNAm levels and ALS age of onset (n=249). Three CpGs (cg03333305, cg15625495, cg26966808) remained significant after adjustment. Non-Finnish European minor allele frequencies (MAF) were extracted from the gnomAD database.     There is no significant difference in age of onset between male and female patients (P=0.7, MWU test).

Fig. S5. Subgroup analysis in US ALS patients stratified for (a) site of onset, (b) sex and (c) familial history.
Patients with bulbar onset had significantly later onset than patients with limb onset (P=2.2× 10 -16 ). Familial ALS patients had a significantly earlier onset than sporadic ALS patients (P=0.001). Female ALS patients had significantly later onset than male patients (P=3.1×10 -13 ).

Fig. S7. Pooled analysis of the association between rs4970944 genotypes and ALS age of onset.
In the pooled ALS sample set (n=4629), rs4970944 genotypes are significantly associated with age of onset (P=0.001, adjusted for sex, site of onset and family history). Each A-allele is associated with a 0.9 year later onset. Fig. S8. Meta-analysis of the adjusted regression coefficient from the discovery cohort (n=469) and the replication cohort (n=3697) in C9orf72 negative ALS patients. It confirmed the significant association between rs4970944 and age of onset (pooled B=0.9, P=0.0015) in C9orf72 negative ALS patients.

Supplementary acknowledgements
The dataset(s) used for the analyses described in this manuscript were obtained from the Age-Related Eye Disease Study (AREDS) Database found at https://www.nei.nih.gov/research/clinical-trials/age-related-eye-disease-studyareds through dbGaP accession number phs000001.v3.p1. Funding support for AREDS was provided by the National Eye Institute (N01-EY-0-2127). We would like to thank the AREDS participants and the AREDS Research Group for their valuable contribution to this research.
The Framingham Heart Study is conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with Boston University (Contract No. N01-HC-25195 and HHSN268201500001I). This manuscript was not prepared in collaboration with investigators of the Framingham Heart Study and does not necessarily reflect the opinions or views of the Framingham Heart Study, Boston University, or NHLBI. Funding to support the Omni cohort recruitment, retention and examination was provided by NHLBI Contract N01-HC-25195 and HHSN268201500001I, as well as NHLBI grants R01-HL070100, R01-HL076784, R01-HL-49869, and U01-HL-053941.
Research support to collect data and develop an application to support this project was provided by 3P50CA093459, 5P50CA097007, 5R01ES011740, and 5R01CA133996.
The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. This manuscript was not prepared in collaboration with investigators of the WHI, has not been reviewed and/or approved by the Women's Health Initiative (WHI), and does not necessarily reflect the opinions of the WHI investigators or the NHLBI. Funding support for WHI GARNET was provided through the NHGRI Genomics and Randomized Trials Network (GARNET) (Grant Number U01 HG005152). Assistance with phenotype harmonization and genotype cleaning, as well as with general study coordination, was provided by the GARNET Coordinating Center (U01 HG005157). Assistance with data cleaning was provided by the National Center for Biotechnology Information. Funding support for genotyping, which was performed at the Broad Institute of MIT and Harvard, was provided by the NIH Genes, Environment and Health Initiative [GEI] (U01 HG004424). The datasets used for the analyses described in this manuscript were obtained from dbGaP at http://www.ncbi.nlm.nih.gov/sites/entrez?db=gap through dbGaP accession phs000001, phs000007, phs000187, phs000196, phs000200, phs000292, phs000304, phs000315, phs000368, phs000372, phs000394, phs000397, phs000404, phs000421, phs000428, phs000615, phs000675, phs000801, and phs000869. Funding support for the Genes and Blood Clotting Study was provided through the NIH/NHLBI (R37 HL039693). The Genes and Blood Clotting Study is one of the Phase 3 studies as part of the Gene Environment Association Studies (GENEVA) under GEI. Assistance with genotype cleaning was provided by the GENEVA Coordinating Center (U01 HG004446). Funding support for DNA extraction and genotyping, which was performed at the Broad Institute, was provided by NIH/NHLBI (R37 HL039693). Additional support was provided by the Howard Hughes Medical Institute.
The dataset(s) used for the analyses described in this manuscript were obtained from the database of Genotype and Phenotype (dbGaP) found at http://www.ncbi.nlm.nih.gov/gap through dbGaP accession number phs000368. Samples and associated phenotype data for the Genome-Wide Association Scan [GWAS] of Polycystic Ovary Syndrome Phenotypes were provided by Andrea Dunaif, M.D.